All community members are invited to attend our 8th interview symposium. It will feature scientific talks from our applicants, several talks from our current Ph.D. scholars, and two faculty keynotes.
Each year, IMPRS-IS hosts an interview symposium to interview and recruit new Ph.D. students.
The 2024 event will feature scientific talks from the applicants, as well as two keynotes by our faculty members Dr. Wieland Brendel and Dr. Andreas Bulling.
A detailed event schedule is available to community members now from our interviews website: https://interviews.imprs.is.mpg.de/
All applicants, IMPRS-IS scholars, faculty, and associated faculty are granted access to the website link above. Since this is a closed event, only community members can view our interviews website and must first register for an account before gaining access.
The event keynotes are open to a more general audience. Details on how to join can be found below.
Date: Thursday, February 8
Time: 15:30 - 16:30 CET
Onsite Location: MPI-IS Tübingen, Main Lecture Hall, Room N0.002
Talk Title: Cracking the black box: how far are we from understanding the inner workings of deep vision models?
Abstract: How do deep vision models recognize a car? How do they differentiate between cats and dogs? Why do they sometimes fail in peculiar ways? Although the gap between humans and machines has significantly narrowed on a behavioral level, we are still largely in the dark about their exact inner workings. In this talk, I will discuss some recent progress we and others have made in shedding light on these black boxes and will highlight some open challenges we need to overcome. Additionally, I will also highlight a few of our failed attempts, hypotheses, and experiments as a gentle reminder that behind the success stories often seen in publications, there are many more trials and errors that pave the way. These missteps are not just setbacks, but rather essential steps in the journey towards breakthroughs and understanding.
Biography: Wieland Brendel received his Diploma in physics from the University of Regensburg (2010) and his Ph.D. in computational neuroscience from the École normale supérieure in Paris (2014). He joined the University of Tübingen as a postdoctoral researcher in the group of Matthias Bethge, became a Principal Investigator and Team Lead in the Tübingen AI Center (2018) and an Emmy Noether Group Leader for Robust Machine Learning (2020). In May 2022, Wieland joined the Max-Planck Institute for Intelligent Systems as an independent Group Leader and is now a Hector-endowed Fellow at the ELLIS Institute Tübingen (since September 2023). He received the 2023 German Pattern Recognition Award for his substantial contributions on robust, generalisable and interpretable machine vision. Aside of his research, Wieland co-founded a nationwide school competition (bw-ki.de) and a machine learning startup focused on visual quality control (maddox.ai).
Date: Thursday, February 8
Time: 16:30 - 17:30 CET
Onsite Location: MPI-IS Stuttgart, Copper Lecture Hall, Room 2R04
Talk Title: The academic journey - a personal travel report
Abstract: Doing a PhD is clearly a very important, but also only the first in a long sequence of steps required when embarking on the journey of becoming an academic. While seemingly somewhere between fully under our control or completely unpredictable, many career steps along the way merely follow opportunities presented to us by people we meet or places we go to. But the impact of these decisions typically only becomes clear in retrospective, causing uncertainty. Similarly, research interests and emphases change over time, partly as a result of these encounters and decisions. In my talk I will provide an anecdotal "travel report" of my personal academic journey so far. I will try to provide insights into the reasoning behind some of the steps I took, opportunities I did (not) take, and the impact these decisions had. Based on these experiences, I will also try to advise on what I personally think is important to be successful on this journey. All garnished with examples of my research that is (obviously) closely linked to these steps and decisions. Overall, I hope to provide encouragement for those at the beginning of this (long) journey, maybe even to still some of their fears, but also to provide a realistic and thus hopefully practically useful view on what it takes to become an academic.
Biography: Andreas Bulling is Full Professor (W3) of Computer Science at the University of Stuttgart and Director of the research group Human-Computer Interaction and Cognitive Systems. He is also an ELLIS Fellow and Founding Director of the Stuttgart ELLIS unit, Faculty and Member of the Executive Board of the International Max Planck Research School for Intelligent Systems (IMPRS-IS), and Member in the Cluster of Excellence "Data-integrated Simulation Science" (SimTech) as well as the Stuttgart Interchange Forum for Reflecting on Intelligent Systems (IRIS). He received his MSc. in Computer Science from the Karlsruhe Institute of Technology (KIT), Germany, and a PhD in Information Technology and Electrical Engineering from ETH Zurich, Switzerland. Andreas was previously a Feodor Lynen and a Marie Curie Research Fellow in the Computer Laboratory at the University of Cambridge, UK, and a postdoctoral research associate in the School of Computing and Communications at Lancaster University, UK. Before coming to Stuttgart, he was a Senior Researcher at the Max Planck Institute for Informatics and an Independent Research Group Leader (W2) at the Cluster of Excellence on Multimodal Computing and Interaction (MMCI) at Saarland University. He received an ERC Starting Grant in 2018. Group website: https://perceptualui.org/
Participants can watch these talks on-site in either Stuttgart or Tübingen. One talk will be presented live in each location, and the other will be streamed remotely in real time. Both talks can also be watched online via Webex, which is how we anticipate most applicants will join.
For details about this event or questions about gaining access to the interviews website, please email us (firstname.lastname@example.org).
Photo credit: MPI für Intelligent Systeme